Species Distribution Models of the Spartina alterniflora Loisel in Its Origin and Invasive Country Reveal an Ecological Niche Shift

Abstract

Spartina alterniflora is a perennial herb native to the American Atlantic coast and is the dominant plant in coastal intertidal wetlands. Since its introduction to China in 1979, it has quickly spread along the coast and has caused various hazards. To control the further spread of S. alterniflora in China, we first reconstructed the history of the spread of S. alterniflora in its invasion and origin countries. We found that S. alterniflora spreads from the central coast to both sides of the coast in China, while it spreads from the west coast to the east coast in America. Furthermore, by comparing 19 environmental variables of S. alterniflora in its invasion and origin countries, it was found that S. alterniflora is more and more adaptable to the high temperature and dry environment in the invasion country. Finally, we predicted the suitable areas for this species in China and America using the maximum entropy (MaxEnt) model and ArcGIS. Overall, through analysis on the dynamic and trend of environmental characteristics during the invasion of S. alterniflora and predicting its suitable area in the invasion area, it guides preventing its reintroduction and preventing its further spread of the species has been found. It has reference significance for studying other similar alien plants and essential enlightening relevance to its invasion and spread in similar areas.

Differences in carbon sink capacity and carbon storage of several typical modified tidal wetlands in the Yangtze River Estuary

“…These ndings suggested that wetlands with high salinity and low elevation are more suitable for S. alterni ora growth. Similar ndings have also been reported by (Yuan et al, 2021), who found that the strong salt tolerance of S. alterni ora is an excellent adaptation of plants in coastal wetlands to salinity environment.…”

Prediction of Potential Suitable Distribution Areas of Quasipaa spinosa in China Based on MaxEnt Optimization Model

“…Q. spinosa distribution occurrence data and selected environmental variables were loaded into the MaxEnt model. The data were randomly divided: 75% of the location point data were used as a training model, with the remaining 25% used for validating the MaxEnt model [ 37 , 38 ]. By default, the maximum number of iterations was set as 10,000, the model was repeated for 10 times, and the predicted results were output in “Cloglog” format and “asc” file type [ 39 ].…”

Habitat protection and planning for Leonurus japonicus using the Maxent and Marxan models

“…The software ENMTools v1.4 was used to calculate the niche breadth in the geographical and environmental space of each period as the average Levins B1 (inverse concentration) and B2 (uncertainty) values of the habitat suitability map for each period (Warren et al, 2008;Levins et al, 1968). Levins B1 and B2 values range from 0 to 1, with values close to 0 representing a narrow niche breadth and values close to 1 representing a wide niche breadth (Yuan et al, 2021).…”

“…The size of niche overlap reflects the similarity of plant utilization resources. Large niche overlap indicates that they have similar ecological adaptability, resource utilization, and biological characteristics under certain environmental conditions (Yuan et al, 2021). Compared with the population distribution in the current period, the D value of the population distribution in the future period is greater than 0.6; the degree of niche overlap is large; the adaptability to habitat resources is similar, and the resource competition is fierce, so there is no significant niche differentiation.…”